Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4968099 | Journal of Informetrics | 2017 | 15 Pages |
Abstract
Employing the machine learning method, this study analyses 6504 articles from four major newspapers, New York Times, Washington Post, USA Today, and The Guardian, to examine how media cover the topic about causes of autism. A total of 14,305 causal sentences on the topic are extracted from media articles and subjected to analysis of causal entities and descriptions. Results show media have presented multiple factors (e.g. vaccination, genetics, and parenting) pertaining to the causes of autism, as well as multiple symptoms of autism. Most of those causal relationships are presented in a tentative or uncertain manner. The study also reveals significant differences in reportage of autism causation across time and media channels.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Yujia Zhai, Shaojing Sun, Fang Wang, Ying Ding,